Articles | Volume 3, issue 2
https://doi.org/10.5194/wes-3-883-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-3-883-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Nov 2018
Research article |
| 16 Nov 2018
| 16 Nov 2018
Blind test comparison on the wake behind a yawed wind turbine
Franz Mühle
CORRESPONDING AUTHOR
Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway
Jannik Schottler
ForWind – Center for Wind Energy, Institute of Physics, University of Oldenburg, Oldenburg, Germany
Jan Bartl
Department of Energy and Process Engineering, Norwegian University of Science and Technology, Trondheim, Norway
Romain Futrzynski
Siemens PLM Software, London, UK
Steve Evans
Siemens PLM Software, London, UK
Luca Bernini
Department of Mechanical Engineering, Politecnico di Milano, Milan, Italy
Paolo Schito
Department of Mechanical Engineering, Politecnico di Milano, Milan, Italy
Martín Draper
Facultad de Ingeniería, Universidad de la República, Montevideo, Uruguay
Andrés Guggeri
Facultad de Ingeniería, Universidad de la República, Montevideo, Uruguay
Elektra Kleusberg
Linné FLOW Centre and Swedish e-Science Research Centre (SeRC), Department of Mechanics, KTH Royal Institute of Technology, Stockholm, Sweden
Dan S. Henningson
Linné FLOW Centre and Swedish e-Science Research Centre (SeRC), Department of Mechanics, KTH Royal Institute of Technology, Stockholm, Sweden
Michael Hölling
ForWind – Center for Wind Energy, Institute of Physics, University of Oldenburg, Oldenburg, Germany
Joachim Peinke
ForWind – Center for Wind Energy, Institute of Physics, University of Oldenburg, Oldenburg, Germany
Fraunhofer IWES, Oldenburg, Germany
Muyiwa S. Adaramola
Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway
Lars Sætran
Department of Energy and Process Engineering, Norwegian University of Science and Technology, Trondheim, Norway
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Cited
29 citations as recorded by crossref.
- Numerical Simulation of Turbulent Jet Scour through Implementation of a Single Phase Eulerian Model M. Mendina & G. Usera https://doi.org/10.1061/(ASCE)IR.1943-4774.0001650
- Vortex interaction in the wake of a two- and three-bladed wind turbine J. Bartl et al. https://doi.org/10.1088/1742-6596/1669/1/012027
- A dynamic model of wind turbine yaw for active farm control G. Starke et al. https://doi.org/10.1002/we.2884
- Tip‐vortex breakdown of wind turbines subject to shear E. Kleusberg et al. https://doi.org/10.1002/we.2403
- Large Eddy Simulation of an Onshore Wind Farm with the Actuator Line Model Including Wind Turbine’s Control below and above Rated Wind Speed A. Guggeri & M. Draper https://doi.org/10.3390/en12183508
- High-fidelity wind farm simulation methodology with experimental validation A. Hsieh et al. https://doi.org/10.1016/j.jweia.2021.104754
- A blind test on wind turbine wake modelling: Benchmark results and Phase II announcement I. Chondromatidis et al. https://doi.org/10.1088/1742-6596/3016/1/012035
- The actuator line method for wind turbine modelling applied in a variational multiscale framework M. Ravensbergen et al. https://doi.org/10.1016/j.compfluid.2020.104465
- Stability of Floating Wind Turbine Wakes V. Kleine et al. https://doi.org/10.1088/1742-6596/1934/1/012009
- Large-scale horizontal axis wind turbine aerodynamic efficiency optimization using active flow control and synthetic jets A. Nabhani et al. https://doi.org/10.1016/j.energy.2025.134940
- Non-iterative vortex-based smearing correction for the actuator line method V. Kleine et al. https://doi.org/10.1017/jfm.2023.237
- Simulation of a Hydrostatic Pressure Machine with Caffa3d Solver: Numerical Model Characterization and Evaluation R. Pienika et al. https://doi.org/10.3390/w12092419
- A blind test on wind turbine wake modelling based on wind tunnel experiments: Phase I – The benchmark case V. Pappa et al. https://doi.org/10.1088/1742-6596/2767/9/092053
- Parametric dependencies of the yawed wind‐turbine wake development E. Kleusberg et al. https://doi.org/10.1002/we.2395
- Review of Turbine Parameterization Models for Large-Eddy Simulation of Wind Turbine Wakes Z. Li et al. https://doi.org/10.3390/en15186533
- Investigating the impact of numerical uncertainties in CFD-generated training data on neural network models for wind-turbine wake predictions M. Ye et al. https://doi.org/10.1016/j.oceaneng.2025.123200
- Actuator line method applied to grid turbulence generation for large-Eddy simulations F. Houtin-Mongrolle et al. https://doi.org/10.1080/14685248.2020.1803495
- Influence of limiting the projection region on coarse Large Eddy Simulation-Actuator Line Model simulations M. Draper et al. https://doi.org/10.1088/1742-6596/1618/2/022051
- Design of twist-modified lab-scale wind turbine rotors for enhanced wake recovery V. Sellevold et al. https://doi.org/10.1088/1742-6596/3016/1/012006
- Large eddy simulation of an onshore wind farm under different operating regimes including topographic effects M. Draper et al. https://doi.org/10.1088/1742-6596/2265/2/022039
- Tip-vortex instabilities of two in-line wind turbines V. Kleine et al. https://doi.org/10.1088/1742-6596/1256/1/012015
- The near-wake development of a wind turbine operating in stalled conditions – Part 1: Assessment of numerical models P. Weihing et al. https://doi.org/10.5194/wes-9-933-2024
- Cooperative yaw control of wind farm using a double-layer machine learning framework S. Yang et al. https://doi.org/10.1016/j.renene.2022.04.104
- Optimal closed-loop wake steering – Part 1: Conventionally neutral atmospheric boundary layer conditions M. Howland et al. https://doi.org/10.5194/wes-5-1315-2020
- CFD Analysis of a Hydrostatic Pressure Machine with an Open Source Solver R. Pienika et al. https://doi.org/10.3390/fluids8010009
- Analysis of Near-Wake Deflection Characteristics of Horizontal Axis Wind Turbine Tower under Yaw State Z. Liu et al. https://doi.org/10.32604/EE.2021.016357
- Use of machine learning to optimize actuator configuration on an airfoil M. Tadjfar et al. https://doi.org/10.1016/j.jfluidstructs.2024.104141
- Assessment of a heterogeneous computing CFD code in wind farm simulations B. López et al. https://doi.org/10.1088/1742-6596/2265/4/042046
- The stability of wakes of floating wind turbines V. Kleine et al. https://doi.org/10.1063/5.0092267
29 citations as recorded by crossref.
- Numerical Simulation of Turbulent Jet Scour through Implementation of a Single Phase Eulerian Model M. Mendina & G. Usera https://doi.org/10.1061/(ASCE)IR.1943-4774.0001650
- Vortex interaction in the wake of a two- and three-bladed wind turbine J. Bartl et al. https://doi.org/10.1088/1742-6596/1669/1/012027
- A dynamic model of wind turbine yaw for active farm control G. Starke et al. https://doi.org/10.1002/we.2884
- Tip‐vortex breakdown of wind turbines subject to shear E. Kleusberg et al. https://doi.org/10.1002/we.2403
- Large Eddy Simulation of an Onshore Wind Farm with the Actuator Line Model Including Wind Turbine’s Control below and above Rated Wind Speed A. Guggeri & M. Draper https://doi.org/10.3390/en12183508
- High-fidelity wind farm simulation methodology with experimental validation A. Hsieh et al. https://doi.org/10.1016/j.jweia.2021.104754
- A blind test on wind turbine wake modelling: Benchmark results and Phase II announcement I. Chondromatidis et al. https://doi.org/10.1088/1742-6596/3016/1/012035
- The actuator line method for wind turbine modelling applied in a variational multiscale framework M. Ravensbergen et al. https://doi.org/10.1016/j.compfluid.2020.104465
- Stability of Floating Wind Turbine Wakes V. Kleine et al. https://doi.org/10.1088/1742-6596/1934/1/012009
- Large-scale horizontal axis wind turbine aerodynamic efficiency optimization using active flow control and synthetic jets A. Nabhani et al. https://doi.org/10.1016/j.energy.2025.134940
- Non-iterative vortex-based smearing correction for the actuator line method V. Kleine et al. https://doi.org/10.1017/jfm.2023.237
- Simulation of a Hydrostatic Pressure Machine with Caffa3d Solver: Numerical Model Characterization and Evaluation R. Pienika et al. https://doi.org/10.3390/w12092419
- A blind test on wind turbine wake modelling based on wind tunnel experiments: Phase I – The benchmark case V. Pappa et al. https://doi.org/10.1088/1742-6596/2767/9/092053
- Parametric dependencies of the yawed wind‐turbine wake development E. Kleusberg et al. https://doi.org/10.1002/we.2395
- Review of Turbine Parameterization Models for Large-Eddy Simulation of Wind Turbine Wakes Z. Li et al. https://doi.org/10.3390/en15186533
- Investigating the impact of numerical uncertainties in CFD-generated training data on neural network models for wind-turbine wake predictions M. Ye et al. https://doi.org/10.1016/j.oceaneng.2025.123200
- Actuator line method applied to grid turbulence generation for large-Eddy simulations F. Houtin-Mongrolle et al. https://doi.org/10.1080/14685248.2020.1803495
- Influence of limiting the projection region on coarse Large Eddy Simulation-Actuator Line Model simulations M. Draper et al. https://doi.org/10.1088/1742-6596/1618/2/022051
- Design of twist-modified lab-scale wind turbine rotors for enhanced wake recovery V. Sellevold et al. https://doi.org/10.1088/1742-6596/3016/1/012006
- Large eddy simulation of an onshore wind farm under different operating regimes including topographic effects M. Draper et al. https://doi.org/10.1088/1742-6596/2265/2/022039
- Tip-vortex instabilities of two in-line wind turbines V. Kleine et al. https://doi.org/10.1088/1742-6596/1256/1/012015
- The near-wake development of a wind turbine operating in stalled conditions – Part 1: Assessment of numerical models P. Weihing et al. https://doi.org/10.5194/wes-9-933-2024
- Cooperative yaw control of wind farm using a double-layer machine learning framework S. Yang et al. https://doi.org/10.1016/j.renene.2022.04.104
- Optimal closed-loop wake steering – Part 1: Conventionally neutral atmospheric boundary layer conditions M. Howland et al. https://doi.org/10.5194/wes-5-1315-2020
- CFD Analysis of a Hydrostatic Pressure Machine with an Open Source Solver R. Pienika et al. https://doi.org/10.3390/fluids8010009
- Analysis of Near-Wake Deflection Characteristics of Horizontal Axis Wind Turbine Tower under Yaw State Z. Liu et al. https://doi.org/10.32604/EE.2021.016357
- Use of machine learning to optimize actuator configuration on an airfoil M. Tadjfar et al. https://doi.org/10.1016/j.jfluidstructs.2024.104141
- Assessment of a heterogeneous computing CFD code in wind farm simulations B. López et al. https://doi.org/10.1088/1742-6596/2265/4/042046
- The stability of wakes of floating wind turbines V. Kleine et al. https://doi.org/10.1063/5.0092267
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